7 Page : 7 1 Introduction 1.1 Background The GlobColour project started in 2005 as an ESA Data User Element (DUE) project to provide a continuous data set of merged L3 Ocean Colour products. Merging outputs from different sensors ensures data continuity, improves spatial and temporal coverage and reduces data noise. This allows in particular to process long time series of consistent products (trend analysis, climatology, data assimilation for model hindcast). Since then, ACRI has maintained the archive and Near Real Time data access services through the Hermes website; knowing that in the frame of MyOcean, a sub-set (Chl, reflectances, Secchi depth) is produced at global scale and in Near Real Time by the OCTAC Processing Unit. The reprocessing and the update of the Hermes interface were performed in the framework of the OSS2015 project, with funding from the EU FP7 under grant n The GlobColour project has received additional funding from European Union FP7 under grant agreement n (MyOcean) and from PACA Region under project RegiColour In addition, support from NASA regarding access to L2 products is acknowledged. The GlobColour primary data set has now been delivered as a Group on Earth Observations System of Systems (GEOSS) core data set under reference: urn:geoss:csr:resource:urn:uuid:4e33fd81-d5cc-dc40-b645-ab961447d9d Scope of the document This User Guide contains a description of: the products content - the parameters - the spatial and temporal coverage - the processing system the products format Hermes interface user s guide Appendices containing additional information on products and processing

23 Page : WVCS Category Atmosphere PARAMETER WVCS Description WVCS is the total water vapor column over clear sky (g/cm²) coming from the MERIS L2 data. Water vapour is the most effective greenhouse gas in the atmosphere. It influences weather and climate and is responsible for cloud development, precipitation, and modulates the atmospheric radiative energy transfer. L3 merging method AV Sensor availability MER Algorithm Reference WCVS is an average of the corresponding MERIS product which uses a polynomial function of several band ratios. MERIS ATBD References https://earth.esa.int/handbooks/meris/cntr2-7.htm (accessed December 2014)

25 Page : 25 T865 (Water) Algorithm T443 is computed from the MERIS L2 product. T865 is merged from corresponding L2 products for the various sensors. T550 is extrapolated from the land and water products using the corresponding Angström exponent: T550 = Txxx * (550 / xxx) - with =1 for land (xxx=443) and =A865 for water (xxx=865) Reference Gordon, 1997 MERIS ATBD Validity The GlobColour merged atmosphere products are not yet validated. The validity of the products is not certified. References Gordon, H.R., Atmospheric correction of ocean color imagery in the Earth Observing System era. Journal of Geophysical Research Atmospheres 102 (D14), MERIS ATBD: https://earth.esa.int/handbooks/meris/cntr2-7.htm (accessed December 2014)

37 Page : KD490 Category Ocean Subsurface Optical PARAMETER KD490, KD490-LEE Description L3 merging method Sensor availability Kd(490) is the diffuse attenuation coefficient (m -1 ) of the downwelling irradiance at 490 nm. It is one indicator of the turbidity of the water column. KD490 is computed according to the Morel algorithm, while KD490-LEE is computed from the Lee and Arnone algorithm. AN MER MOD SWF VIR KD490 (Morel)

41 Page : ZEU Category Ocean Subsurface Optical PARAMETER ZEU Description L3 merging method Sensor availability ZEU is the depth of the euphotic layer (m), i.e. the depth for which the down-welling irradiance is 1% of its value at the surface. It characterizes the upper layer of the ocean which can support phytoplankton photosynthesis. It depends on the turbidity of the water. AN MER MOD SWF VIR Algorithm Reference ZEU computed from the corresponding merged CHL1 products (weighted method), using the following empirical equation: ZEU = y y y 3 with y = log 10 (CHL1) Morel et al References Morel, A., Huot, Y., Gentili, B., Werdell, P.J., Hooker, S.B. and B.A. Franz (2007). Examining the consistency of products derived from various ocean color sensors in open ocean (Case 1) waters in the perspective of a multi-sensor approach. Remote Sensing of Environment, 111, ZHL is computed from KD490. Related products

42 Page : ZSD Category Ocean Subsurface Optical PARAMETER ZSD, ZSD-DORON Description L3 merging method Sensor availability ZSD is the Secchi Disk depth (m). It represents the maximum depth at which a calibrated black and white disk (the so-called Secchi disk) is still visible from the surface. As such, it is a good indication of the maximum depth of underwater vertical visibility. Two algorithms are available. ZSD is computed according to the Morel et al. algorithm, and ZSD-DORON according to Doron et al. AN MER MOD SWF VIR ZSD (Morel et al.)

53 Page : The spatial and temporal coverage The binned products The GlobColour level-3 binned products have a resolution of 1/24 at the equator (i.e. around 4.63 km) for global products and of 1/96 (i.e. around 1.16 km) for Europe products. They consist of the accumulated data of all merged level 2 products, corresponding to periods of one day (a data-day algorithm is applied), 8 days and a calendar month. 8-days binning periods are continuous, starting from the first day of each calendar year. The geographical location and extend of each bin is determined by the so-called Integerized Sinusoidal (ISIN) grid. The complete ISIN grid definition is provided in appendix. In GlobColour binned ISIN products, bins are always written in sequential order, from the southernmost-westernmost bin to the northernmost-easternmost bin. Only valid bins are written in a binned product. Bins with no contributions (i.e. uncovered bins) are not contained in the files as well as the covered bins where no valid data has been found. The spatial resolutions of global and Europe products yield to the following grid characteristics: Area GLOBAL Europe Average bin size: 4.63 km 1.16 km Average bin area: km km 2 Total number of rows in the grid: 4320 Number of columns at equator: 8640 Number of columns at poles: 3 Total number of bins in the grid: 23,761,676 28,307, The mapped products Table 2-5: Main characteristics of the ISIN grids The GlobColour level-3 mapped products have a resolution of 1/24, 0.25 or 1.0 (i.e. respectively around 4.63 km, 28 km and 111 km at the equator) for global products and of x0.01 for Europe products. They consist of the flux-conserving resampling of the global level-3 binned products. Daily, 8-days and monthly products are available. Quicklooks of these products are available in PNG format.

54 Page : Overall description of the processor 3 The GlobColour system The GlobColour processor is the computation element of the GlobColour processing system. Its function is the transformation of EO level 2 products (or level 3 products) from independent instrument/missions into a single merged level 3 product. The level-2 products are transformed after the sensor-specific preprocessing to the global and Europe ISIN grids. This binning is separately applied to each level-2 input product for each instrument. Outputs are intermediate spatially binned level-3 products for each instrument, also called level 3 at track level. The term binning refers to the process of distributing the contributions of the level-2 pixels in satellite coordinates to a fixed level-3 grid using a geographic reference system. When images of different resolutions are to be accumulated together, if the spatial coverage of each pixel is not taken into account, the importance of the image of the highest resolution are largely predominant over the images of smaller resolutions; this may result in introducing a bias in the final product. Computing a flux value associated to each pixel may solve that problem. Assuming that the data flux for each input pixel is constant, the resampling problem is actually reduced to the problem of finding the set of pixels overlapping each level-3 bin, and then calculating the relative overlapped area. This approach not only allows to properly mix data of various resolutions together, it also allows to distribute data properly among different level-3 bins as the input image pixel is usually overlapping several of them. This also makes it possible to produce level-3 data at a higher resolution than the input data with no "holes". Though very attractive, the major drawback to this method is that it is significantly slower than the usual method; different techniques are being investigated to increase the speed of this approach. The algorithm implemented in the GlobColour processing chain uses the fast Sutherland- Hodgeman area clipping. For more information on the algorithm used refer to ["A fast fluxconserving resampling algorithm", available at The same binning algorithm is applied to each kind of input variables. Only the flags taken into account when filtering the data are different. These flags are listed in the next subsection. Following this logic, the GlobColour processor is mainly composed of 4 separate modules, namely: 1. a preprocessor module 2. a spatial binning module 3. a merging module 4. a temporal binning module For each sensor, a pre-processing is foreseen just after extraction of the L2. This preprocessor serves for example in the case of MERIS and wherever requested to transform the L2 normalised water leaving reflectances into fully normalised remote sensing

57 Page : 57 (pp4): MODIS, SeaWiFS and VIIRS L2 products now provide LAT/LON for each pixel but SZA and SAA are not available so the preprocessor recomputed them from pixel position and date/time. The following tables list, for each instrument, all variables coming from the preprocessing module, their symbols and their associated validity equation(s). For all sensors we consider that a pixel is invalid if the absolute value of its sun zenith angle is greater than MERIS For all MERIS products we discard input Level-2 pixels with packed value equal to 0 (except for the flags band). Acronym Variable Validity equation NRRSxxx RRSxxx CHL1 CHL2 CDM TSM WVCS T865 A865 T443 A443 Fully (or None) normalised remote sensing reflectance at xxx nm Chlorophyll concentration OC4Me Chlorophyll concentration C2R NN Coloured dissolved and detrital organic materials absorption coefficient C2R NN Total suspended matter concentration C2R NN Total water vapor column over clear sky Aerosol optical thickness over water Angstrom alpha coefficient over water Aerosol optical thickness over land Angstrom alpha coefficient over land CF Cloud fraction not LAND WATER and not (HIGH_GLINT or ABSOA_DUST or PCD_19_WHITECAPS15 [Note 1] or CLOUD or ICE_HAZE or TOAVI_CSI) with enlarging HIGH_GLINT, CLOUD, ICE_HAZE and TOAVI_CSI by 2 swath pixels WATER and not (HIGH_GLINT or ABSOA_DUST or WHITE_SCATTERER or PCD_15_WHITECAPS15 [Note 1] or CLOUD or ICE_HAZE or TOAVI_CSI) with enlarging HIGH_GLINT, CLOUD, ICE_HAZE and TOAVI_CSI by 2 swath pixels WATER and not (PCD_17 or CLOUD) and not ice from climatology with enlarging CLOUD by 2 swath pixels WATER and not (PCD_16 or CLOUD) and not ice from climatology with enlarging CLOUD by 2 swath pixels not (PCD14 or CLOUD or ICE_HAZE or TOAVI_CSI) with enlarging CLOUD, ICE_HAZE and TOAVI_CSI by 2 swath pixels WATER and not (HIGH_GLINT or PCD_19_WHITECAPS15 [Note 1] or CLOUD or ICE_HAZE or TOAVI_CSI) and [ CASE2_S or not (WHITE_SCATTERER or CASE2_ANOM) ] with enlarging HIGH_GLINT by 2 swath pixels and CLOUD, ICE_HAZE and TOAVI_CSI by 3 swath pixels LAND and not (PCD19 or CLOUD or ICE_HAZE or TOAVI_CSI) and [Note 2] with enlarging CLOUD, ICE_HAZE and TOAVI_CSI by 3 swath pixels

59 Page : MODIS/SeaWiFS/VIIRS Acronym Variable Validity equation NRRSxxx Fully normalised remote sensing reflectance at xxx nm CHL1 CDM POC T865 A865 PIC NFLH PAR Chlorophyll concentration Coloured dissolved and detrital organic materials absorption coefficient at 443 nm Particulate Organic Carbon Aerosol optical thickness over water Angstrom alpha coefficient over water Particulate Inorganic Carbon Normalised Fluorescence Line Height Photosynthetically Available Radiation CF Cloud fraction not LAND not (ATMFAIL or LAND or HILT or HISATZEN or STRAYLIGHT or CLDICE or COCCOLITH or LOWLW or CHLFAIL or CHLWARN or NAVWARN or MAXAERITER or ATMWARN or NAVFAIL or FILTER or HIGLINT) not (ATMFAIL or LAND or HISATZEN or STRAYLIGHT or CLDICE or LOWLW [Note 1] or NAVWARN or ATMWARN or NAVFAIL or FILTER or HIGLINT) [Note 1] (same as for CHL1) and not(prodwarn or MODGLINT) not(land or NAVFAIL or FILTER or HIGLINT) Table 3-3: List of parameters and filters applied to the MODIS/SeaWiFS/VIIRS level 2 data Note 1: ATMWARN is not used for VIIRS The following parameters are included in the geometrical observation condition: Sun zenith angle Sun azimuth angle

60 Page : The spatial and temporal binning schemes The list of steps for the generation of the whole set of GlobColour products is: step 1: L2 to L3 track on ISIN grid step 2: L3 track to L3 daily for each single instrument step 3: L3 daily for each single instrument to merged L3 daily step 4: L3 daily merged to 8days and monthly L3 products step 5: L3 daily/8days/monthly merged products to mapped products on PC grid step 6: generation of the quicklooks These steps are fully described in appendix. The temporal binning algorithm is rather simple and the complexity comes from the selection of the input level-3 products to generate the daily products. The simple, obvious, selection of all data measured between 00:00 and 23:59 leads to possible large temporal aliasing in the same region of observation. The temporal binning process needs the definition of a data-day, as we don't want to mix at the same (or at close geographical locations) pixels observed at too different times. The data-day definition used in the frame of the GlobColour project is fully described in the following sub-chapter. 3.4 The GlobColour data-day approach A new spatial and temporal definition of a data-day has been used in the frame of the GlobColour project. The aim of the data-day definition is to avoid mixing pixels observed at too different times. As for other classic definitions, we accept to increase the duration of a day in order to include the previous and next day data. Then, at the same spatial area we could select the best input, i.e. the one leading to the lowest temporal discrepancies. A dataday therefore may represent data taken over a 24 to 28 hour period. As the Seastar, Aqua, ENVISAT and NPP satellites have different orbits, each of them has its own data-day definition. In the following figures, we have plotted the UTC hour as a function of the pixel longitude for the three instruments for one day in the year. The colour of the dots is proportional to the absolute value of the data latitude (purple-blue for latitude=0 and red-brown for latitude>80 ). The idea behind that representation is that if we want to avoid mixing pixels of different hours of the day at the same longitude, something should be visible on this kind of graphic. We can observe that the data is split in three groups. As expected, the high latitudes of the data cover more longitude values while the equatorial latitudes lead to less scattered longitude values (the orbits are polar). Of course, a bigger width of the instrument track leads to a higher dispersion. We can also observe that the temporal variation of the pixels of each instrument covers a large period of the day, especially for MODIS, SeaWiFS and VIIRS: if we look at the width of the central set of pixels at any longitude, we can see that this width is equal to 8 hours for MERIS, 20 hours for SeaWiFS and 24 hours for MODIS. This is directly linked to the satellite orbit and the track width. If we avoid pixels above 80, the temporal variation decreases to: 8

61 Page : 61 hours for MERIS and SeaWiFS and 16 hours for MODIS. In this new estimation, we have discarded a few valid pixels that belongs to the ascending track (or descending track, depending of the satellite orbit) that are of course far away in longitude with respect to the median part of the track and so will mix with pixels of a previous track, observed several hours before. These groups are attached to three different data-days: the pixels belonging to the median group are attached to the current data-day (i.e. the day given by the current UTC date). the pixels belonging to the upper group are attached to the next data-day the pixels belonging to the lower group are attached to the previous data-day Figure 3-2: MERIS pixels UTC as a function of the pixel longitude (35 days - October 2003)

62 Page : 62 Figure 3-3: MODIS pixels UTC as a function of the pixel longitude (1 day - June 2003) Figure 3-4:SeaWiFS pixels UTC as a function of the pixel longitude (1 day - December 2003) Obviously, we can see on these graphics that the groups are separated by two regular, more or less large white bands. The slope of these bands is equal to -24/360. If we plot a line defined by the crossing nodal time of the satellite at -180 and this slope, we can see that this line is almost always located in the white bands and so can be used to distinguish between data of very different day time at the same longitude.

63 Page : 63 Figure 3-5: Data-day definition line above MODIS pixels UTC versus longitude plot. As some instrument are able to observe through the pole, there is not always such full discontinuity between the groups. Anyway, this is only true for pixels at very high latitudes (>80 ), as shown on the following figure where we have plotted only one SeaWiFS track and the data-day separation line. Figure 3-6: Data-day definition line above one SeaWiFS track. Despite this limitation, there are several reasons to use this data-day separation lines:

64 Page : 64 the observation will be probably flagged due to the limitation in sun zenith angle (70 ) the data is not lost. Only few pixels are shifted to the next of previous data-day the coding is very simple The implementation of this data-day definition is described here: Input parameters: Variable Unit Description CNT hour crossing nodal time in ascending track hr/ slope of the data-day definition lines d UTC date UTC date (day) of the measured pixel h UTC hour UTC date (hour) of the measured pixel deg longitude of the measured pixel Table 3-4: Input parameters for data-day classification Note: has a constant value equal to -24/360. Algorithm: Instrument MODIS (Aqua) VIIRS (NPP) SeaWiFS (SeaStar) MERIS (Envisat) CNT if ( h < CNT + ( +180)* ) then pixel is attached to data-day (d-1) else if ( h > CNT + ( +180)* + 24) then else end if pixel is attached to data-day (d+1) pixel is attached to data-day (d) Table 3-5: CNT of satellites

65 Page : 65 4 The products format 4.1 General rules The GlobColour Level-3 binning scheme and its output products have been designed with respect to a number of widely used definitions and de-facto standards: - netcdf Climate and Forecast Metadata Conventions CF - NASA Ocean Color Level-3 products - GHRSST-PP Level-4 products - IOCCG Report number 4 GlobColour Level-3 output data includes binned, mapped and quicklook products which are described in the following sections. The binned and mapped products are stored in netcdf-4 files. The netcdf-4 library or third-party tools including netcdf-4 readers must be used to read the GlobColour products. The quicklook products are written in PNG format. netcdf (Network Common Data Form) is a machine-independent, self-describing, binary data format standard for exchanging scientific data. The project homepage is hosted by the Unidata program at the University Corporation for Atmospheric Research (UCAR). They are also the chief source of netcdf software, standards development, updates etc. The format is an open standard (see The version 4 of the netcdf format provides new features which are used for GlobColour products: chunking and internal compression. These two features allow us to distribute files with reduced compressed size and optimized random access: reading a small window on a product needs only to read and decompress the chunks covering it, without decompressing the whole file. Other new feature of netcdf-4 like new unsigned data types and groups are not used for GlobColour products to keep compatibility with the netcdf-3 data model: existing netcdf-3 tools could be easily re-used without any other modification than re-linking the program with the version 4 of the library. Note that the netcdf-4 format is now based on the widely supported HDF5 scientific data format, which means that any HDF5 tool will be also able to read the GlobColour products. The following rules are applied when writing the binned (ISIN grid) and mapped products (PC grid): each parameter is stored in a single file including metadata and accumulated statistical data. global metadata are stored as global attributes accumulated statistical data are stored as variables metadata related to statistical data are stored as variable attributes. 4.2 Naming convention This naming convention is common to all GlobColour products (but not to OSS2015 thirdparty products). The file naming convention of the files follows the following rules: where: Lzz_date_time_ROI_SR_INS_PRD_TC_nn.ext - Lzz is the product level (L3b for level 3 binned ISIN grid, L3m for level 3 mapped grid)

66 Page : 66 - date is specified in UTC format as yyyymmdd[-yyyymmdd]. The end date is optional for track and daily products. - time is specified in UTC format as hhmmss[-duration]. The time field is needed only for track products. The duration is expressed in seconds. - ROI is the name of the region of interest (e.g. GLOB for global coverage, EURO for Europe area). - SR indicates the resolution of the grid (e.g. 4 for 1/24 ISIN grid). - INS is the instrument acronym (MER for MERIS, MOD for MODIS, SWF for SeaWiFS, VIR for VIIRS, or any combination of these names for the merged products). For the merged products, the instrument acronym is prefixed with the merging method (AV for simple average, AVW for weighted average, GSM for the GSM model). - PRD is the product type (CHL for chlorophyll...). Note that the various parameter algorithms can be indicated in this field using a - delimiter (e.g. CHL1-M01, CHL1-M02). - TC is the time coverage (TR for track-level products, DAY for daily, 8D for 8days, MO for monthly). - nn is a counter. For track products, we store in this counter the data-day in yyyymmdd format. - ext is the file extension (nc for netcdf files, png for PNG files) The number of field is constant. Missing information leads to two adjacent underscores. Examples: L3b_ _ _GLOB_4_MER_NRRS555_TR_ nc L3m_ EURO_1_MOD_CHL1_DAY_00.nc L3b_ GLOB_4_MER_NRRS413_MO_00.nc L3b_ GLOB_4_AV-MERMODSWF_T865_MO_00.nc 4.3 The binned products A netcdf dataset is made up of three basic components: dimensions variables variables attributes global attributes The variables store the actual data, the dimensions give the relevant dimension information for the variables, and the attributes provide auxiliary information about the variables or the dataset itself. Dimensions All variables stored in the ISIN binned product use one of the two dimensions:

67 Page : 67 Bin Row Dimension Number of bins written in the product Parameter Description Number of useful rows in the global ISIN grid (number of row between northernmost and southernmost bins) Table 4-1: Dimensions - binned products Variables ISIN grid location variables (only present in ISIN case). Some variable names are prefixed by the name of the parameter (e.g. CHL1_mean, EL555_weight). Variable Name netcdf Type Nb of bytes Parameter Description row(bin) NC_SHORT or NC_INT (3) 2 or 4 (3) Latitudinal band index of the bins stored in the product, zero based and beginning at south (1) col(bin) NC_SHORT or NC_INT (3) 2 or 4 (3) Longitudinal index of the bins stored in the product, zero based and beginning at west (1) center_lat(row) NC_FLOAT 4 Center latitude for each useful row (1) center_lon(row) NC_FLOAT 4 Center longitude of the first bin (the first bin in the ISIN grid, not the first valid bin) for each useful row (1) lon_step(row) NC_FLOAT 4 Longitude step for each useful row (1) PRM_mean(bin) NC_FLOAT 4 Average value of the binned pixels values PRM_stdev(bin) NC_FLOAT 4 Standard deviation of the square of the binned pixels values PRM_count(bin) NC_SHORT 2 Number of binned pixels PRM_weight(bin) NC_FLOAT 4 Sum of the weights of the binned pixels PRM_flags(bin) NC_SHORT 2 Flags (4) PRM_error(bin) NC_SHORT 2 Error estimation for the geophysical variable (2) Table 4-2: Variables - binned products Note 1: the row(), col(), center_lat, center_lon and lon_step() arrays allow an easier conversion of the bin index into geographical coordinates rather than the global idx() array written in the SeaWiFS and MODIS level 3 products. Equations to compute center longitude and latitude for a bin b are: index = row(b) first_row (first_row is a global attribute) lat(b) = center_lat( index ) lon(b) = center_lon( index ) + col(b) * lon_step( index ) Note 2: the error associated to each bin is computed from representative values of the bin (e.g. arithmetic mean) and observation conditions (e.g. zenith angles) using a LUT read from an external auxiliary file. The error variable is stored only in products where it is significant (i.e. the error bar is not used for simple averaging merging, and so the error is of course not stored). The error bar is stored in 2 bytes integers using the unit 0.01%. The biggest error bar

68 Page : 68 possible in this format is 32767, so if a computed error bar is greater than then it is set to Note 3: these variables type could be NC_SHORT or NC_INT depending on the ISIN grid resolution. Note 4: the quality control is available through a flags array (2 bytes), provided for each bin of each product (source of instrument: all, MODIS only..., green reflectance threshold, mostly cloudy pixel, etc...). The next table contains the current flags definition. A flag is set if its bit is set to 1. The Bit column contains each flag bit number, from the least to the most significant bit of the 2 bytes. Bit Flag code Description 0 NO_MEASUREMENT Bin not covered by any L2 swaths pixel, valid or invalid (out of swaths) 1 INVALID Bin covered, but only by invalid pixel(s) (invalid because L2 flags, clouds, land, ) 2 Not yet used 3 LAND Bin covered by more than 50% of land. If not set, bin is considered as water. (1) (4) 4 CLOUD1 5 CLOUD2 6 DEPTH1 7 DEPTH2 Cloud fraction (2) Water depth (1) (3) 8 TURBID Computed from EL555. TURBID flag is raised when EL555 is greater than 0 9 ICE Bin covered by ice. Computed from an ice climatology. 10 TROPHIC1 11 TROPHIC2 Trophic classification (5) 12 VIIRS VIIRS valid pixel(s) contribute to the bin value 13 SEAWIFS SeaWiFS valid pixel(s) contribute to the bin value 14 MODIS MODIS valid pixel(s) contribute to the bin value 15 MERIS MERIS valid pixel(s) contribute to the bin value Table 4-3: Flags description Note 1: computed using a common global land elevation and ocean bathymetry product (data from ESA). This product is computed at 4.63 km on the global ISIN and PC grids. Note 2: for 8-days or longer periods, cloud fraction flags are not yet defined (flags are currently set to 0). For daily products they define a cloud coverage classification based on the value of the CF product: (CLOUD2=0) + (CLOUD1=0): CF < 5% (CLOUD2=0) + (CLOUD1=1): 5% <= CF < 25% (CLOUD2=1) + (CLOUD1=0): 25% <= CF < 50% (CLOUD2=1) + (CLOUD1=1): CF >= 50% Note 3: (DEPTH2=0) + (DEPTH1=0): depth < 30m (DEPTH2=0) + (DEPTH1=1): 30m <= depth < 200m

69 Page : 69 (DEPTH2=1) + (DEPTH1=0): 200m <= depth < 1000m (DEPTH2=1) + (DEPTH1=1): depth >= 1000m Note 4: it is possible that a bin flagged LAND has a valid parameter value on coastal limits. Note 5: (TROPHIC2=0) + (TROPHIC1=1): Oligotrophic water (TROPHIC2=1) + (TROPHIC1=0): Mesotrophic water (TROPHIC2=1) + (TROPHIC1=1): Eutrophic water Variables attributes The following table lists the variable attributes used in the GlobColour project. These attributes are commonly used to annotate variable in netcdf files and their usage is strongly encouraged by the CF metadata conventions (excepting for pct_characterised_error which is GlobColour specific). Attribute Name netcdf type Attribute Description long_name string A descriptive name that indicates a variable's content. We set it to the Parameter Description of the previous table standard_name string If available, a CF standard name that references a description of variable s content _FillValue same type as variable A value used to indicate array elements containing no valid data units string Text description of the physical units, preferably S.I. Some variables (row, col, count, flags, ) don t have any units attribute pct_characterised_err or NC_FLOAT Characterised error, expressed in % Table 4-4: Variables attributes - binned products Global attributes This section presents the metadata that are written in the main product file. Metadata is stored as global attributes in the netcdf file. General product information Attribute Name netcdf type Attribute Description Conventions string Indicates compatibility with the Climate and Forecast (CF) netcdf convention. CF-1.4 title string A high-level descriptive title for the product product_name string The name of the product without path. product_type string Temporal binning period: e.g. track, "day", "week", 8-day, "month" product_version string Version of the product format product_level NC_SHORT Product level: 3 parameter_code string Parameter short name (e.g. CHL1 )

70 Page : 70 parameter string Parameter long name (e.g. Chlorophyll-a case 1 water ) parameter_algo_list string List of the algorithms name that were used to generate this parameter or input data (comma delimiter, e.g. OC4Me,OC3v5 ) site_name string Name of the region of interest (e.g. GLOB or EURO ) sensor_name string Instrument short name, e.g. MERIS In case of merged product, this field is an acronym of the merging algorithm applied. sensor string Instrument full name, e.g. MEdium Resolution Imaging Spectrometer Instrument In case of merged product, this field describes the merging algorithm applied. sensor_name_list string List of all input data sensors (comma delimiter) software_name string Name of the processing software software_version string Version string of the processing software institution string Processing centre where the product has been generated processing_time string UTC time of generation of the product in the ISO 8601 yyyymmddthhmmssz standard format netcdf_version string The netcdf file format version DPM_reference string Reference to a document describing the model used to generate the data IODD_reference string Reference to a document describing the content and format of the product references string Published or web-based references that describe the data or methods used to produce it contact string A free text string giving the primary contact for information about the data set copyright string Copyright of the product history string Provides an audit trail for modifications to the original data. Wellbehaved generic netcdf filters will automatically append their name and the parameters with which they were invoked to the global history attribute of an input netcdf file. We recommend that each line begin with a timestamp indicating the date and time of day that the program was executed input_files string List of the input products that were used to generate this product (comma delimiter) input_files_reprocessi ngs string List of the reprocessings versions of each input product when available (comma delimiter). The reprocessing version is given by the MPH SOFTWARE_VER attribute for MERIS and by the global HDF "Processing Version" attribute for MODIS, SeaWiFS anf VIIRS. Table 4-5: Global attributes - binned products (1/3)

71 Page : 71 Temporal information Attribute Name netcdf type Attribute Description start_time string UTC date and time of the first valid or invalid measurement falling in the product, in the ISO 8601 yyyymmddthhmmssz standard format end_time string UTC date and time of the last valid or invalid measurement falling in the product, in the ISO 8601 yyyymmddthhmmssz standard format duration_time NC_LONG Duration in seconds between the first and last valid or invalid measurement falling in the product, in the ISO 8601 PTxxxS standard format period_start_day string UTC start day of the binning period in the ISO 8601 yyyymmdd standard format period_end_day string UTC end day of the binning period in the ISO 8601 yyyymmdd standard format period_duration_day NC_LONG Duration in days of the binning period in the ISO 8601 PxxxD standard format Table 4-6: Global attributes - binned products (2/3) Note: the binning period is not identical to the period resulting from the effective time period of the contributing data. And due to the data-day temporal splitting of the data, the binning period could be included in the effective time period. Grid information Attribute Name netcdf type Attribute Description grid_type string Grid used to project the data: Equirectangular or Integerized Sinusoidal Grid spatial_resolution NC_FLOAT Spatial resolution of the product in km nb_equ_bins NC_LONG Number of equatorial bins (used to built the sinusoidal grid) registration NC_LONG Location of characteristic point within bin (5: centre) straddle NC_LONG Indicates if a longitudinal band straddle the equator (0: no and 1: yes; only present in ISIN case) first_row NC_SHORT or NC_INT First useful row, zero based and beginning at south (only present in ISIN case) lat_step NC_FLOAT Latitude step lon_step NC_FLOAT Longitude step (only present in PC case) earth_radius NC_DOUBLE Earth radius in kilometres (used to build the sinusoidal grid) max_north_grid NC_FLOAT Northernmost latitude of the grid (range: -90 to +90 ) (1) max_south_grid NC_FLOAT Southernmost latitude of the grid (range: -90 to +90 ) (1) max_west_grid NC_FLOAT Westernmost longitude of the grid (range: -180 to +180 ) (1) max_east_grid NC_FLOAT Easternmost longitude of the grid (range: -180 to +180 ) (1) northernmost_latitude NC_FLOAT Latitude in degrees of the northernmost side of the northernmost valid bin (range: -90 to +90 ) southernmost_latitude NC_FLOAT Latitude in degrees of the southernmost side of the southernmost

72 Page : 72 Attribute Name netcdf type Attribute Description valid bin (range: -90 to +90 ) westernmost_longitude NC_FLOAT Longitude in degrees of the westernmost side of the westernmost valid bin (range: -180 to +180 ) easternmost_longitude NC_FLOAT Longitude in degrees of the easternmost side of the easternmost valid bin (range: -180 to +180 ) nb_grid_bins NC_LONG Total number of bins of the grid nb_bins NC_LONG Total number of bins saved in the product pct_bins NC_FLOAT (nb_bins * 100) / nb_grid_bins nb_valid_bins NC_LONG Number of valid bins in the product (i.e. bins not equal to _FillValue) pct_valid_bins NC_FLOAT (nb_valid_bins * 100) / nb_bins Table 4-7: Global attributes - binned products (3/3) 4.4 The mapped products The mapped product is the level 3 binned product projected on a Plate-Carrée. This product is created by a re-projection of the level 3 binned data using an equal-angle latitudelongitude projection. Land bins and missing data are represented by a "no-data" value (values identified by the netcdf global _FillValue attribute). There is a one-to-one correspondence between the level 3 binned and mapped products. The averaging periods are the same as for the binned products: daily, 8-days and monthly. The following table gives the grid size as a function of the spatial resolution: Area EURO GLOB Angular resolution 1/96 1/ Longitudinal grid size Latitudinal grid size Table 4-8: Dimensions of the grid - mapped products A PNG representation of the level 3 mapped product is distributed. The format of the PNG file is not described here. The colour scale table is also provided. The layout of the mapped products is similar to the layout of the binned products. Most of the global attributes and variable attributes are identical. The differences are listed below. Dimensions Due to their rectangular grid layout, the mapped products include two dimensions for each variable (instead of a single one for the binned products). The naming of the dimensions refers to the "Independent latitude, longitude, vertical and time axes" definition of the CF convention.

73 Page : 73 Dimension Value Description lon lat Number of pixels in the longitudinal axis of the map grid. A corresponding variable named lon contains the actual longitude values. Number of pixels in the latitudinal axis of the map grid. A corresponding variable named lat contains the actual latitude values. Table 4-9: Dimensions - mapped products With respect to the binned products, the mapped product includes variables to specify the geolocation of the map pixels (for the binned products, the geolocation of the bins shall be recomputed from formulas and parameters provided in the product or read in a specific file). Variable Name netcdf Type Nb of bytes Parameter Description lon(lon) NC_FLOAT 4 Center longitude of each column of the grid, beginning at west. Following the CF convention, the attributes of this variable are: long_name = "longitude" unit = "degrees_east". lat(lat) NC_FLOAT 4 Center latitude of each row of the grid, beginning at north. Following the CF convention, the attributes of this variable are: long_name = "latitude" unit = "degrees_north". Table 4-10: Variables - mapped products (1/2) The definition of the variables is also modified by the fact that 2D maps are written in the products instead of 1D vectors of bins. Note also that the row and col variables needed to locate the bin in the sinusoidal grid is no more needed as all the map is stored in the file. Variable Name netcdf Type Nb of bytes Parameter Description PRM_mean(lat,lon) NC_FLOAT 4 Average value of the binned pixels values PRM_stdev(lat,lon) NC_FLOAT 4 Standard deviation of the square of the binned pixels values PRM_count(lat,lon) NC_SHORT 2 Number of binned pixels PRM_weight(lat,lon) NC_FLOAT 4 Sum of the weights of the binned pixels PRM_flags(lat,lon) NC_SHORT 2 Flags PRM_error(lat,lon) NC_SHORT 2 Error estimation for the geophysical variable Table 4-11: Variables - mapped products (2/2)

74 Page : 74 5 How to? 5.1 Access the GlobColour data The HERMES interface The GlobColour products are also available through the HERMES web interface: Figure 5-1: the HERMES Interface HERMES provides the following access: GlobColour Data Set The GlobColour data set consists of daily, weekly and monthly Level-3 ocean colour products generated at day+30. The archive data is based on the merging of MERIS, SeaWiFS, MODIS and VIIRS level-2 data over the whole globe, with data extraction capability over user-defined areas. OSS 2015 Demonstration products The OSS2015 new EO products are available from a dedicated page.

75 Page : Ordering GlobColour Products Figure 5-2: GlobColour Data Access interface The GlobColour Data Access interface is depicted in Figure 5-2. The selection of the spatial coverage is performed by: Selecting Global (4/25/100 km products) or Europe (1 km) products Selecting an extraction zone (optional) through the interactive map or the coordinate boxes. Use shift+click to select a rectangle on the map. Use to resize the selection zone, and to navigate on the map. The map overlays can be changed by clicking on the + button, see figure below.

76 Page : 76 Check boxes allow selecting: Figure 5-3: Selection of the map overlays Grid type (sinusoidal L3b or Plate-Carrée L3m) Spatial resolution And temporal resolution (binning period). The temporal coverage is adjusted through the interactive calendar. Finally the products selection is performed by checking the corresponding boxes. Once the product order is finished, click on Search to retrieve the products of the database corresponding to the order. A list of products appears on the screen. Products can be deselected or re-selected by clicking on their name in the list. The number of selected products and the estimated size of the order are refreshed automatically. A pre-visualisation of the selected images is possible by clicking on the Visualize button.

78 Page : Ordering OSS2015 demonstration products OSS2015 products can be accessed using a similar but different interface, see Figure 5-5. Figure 5-5: OS2015 products data access Ordering a list of products The products can also be ordered by uploading a list of products in a text file (comma separated). This functionality can be used to generate automatically a list of products using the naming convention. Clicking on the Upload List button opens a file browser to select the file Retrieving the data After completion of the order, the user is asked to provide his/her address. Once the order has been processed, an is sent to the user providing directions to retrieve the data on the GlobColour ftp server.

79 Page : Download the data from the GlobColour ftp server The GlobColour project maintains an ftp site from where the products can be downloaded. Read the information provided by the GlobColour web site ("Data Access" section) to get the latest news about this service. The current ftp server is ftp://ftp.hermes.acri.fr Login and passwords can be obtained by filling the request on-line on the hermes page FTP access. The distribution structure of the ftp archive is: /zone (GLOB EURO) /sensor (seawifs meris modis viirsn merged) /binning period (day 8-day month) /yyyy/mm/dd Each directory contains the netcdf products (L3b*.nc L3m*.nc) as well as the associated quicklook images. The ftp also delivers the third party products (NPP and PFT). A convenient way to download the products is to use the Unix wget command. This command is also available in the cygwin package for Windows systems. wget is particularly efficient to download specific files from scattered sub-directories. It can be used also to check for new products - mirroring (already downloaded files are not transferred, updated products on the server are transferred). Here is an example for downloading all the MERIS CDM binned products. You can adapt this command to your specific needs. The specification of the GlobColour products filenames is useful to use the correct wildcarding included in the wget commands. wget -r -l10 -t10 -A "L3b*_4_*MER_CDM*.nc" -w3 -Q1000m \ Another example to download all the CHL1 monthly quicklooks at 25 km resolution. wget -r -l10 -t10 -A "L3m*_25_*CHL1_MO*.nc" -w3 -Q1000m \ The products will be stored in a local directory called ftp.fr-acri.com using the same structure as on the ftp server. All options of the wget command are described at: The following options are recommended: -w3 is specified to pause the process 3s after each download to decrease our server load by making the requests less frequent. Please keep it to share the bandwidth with other users. -Q1000m limits the amount of data you can retrieve in one command (1 Gb). Please, keep this option too. 5.3 Read the data The products may be read using the netcdf library or any third-party tool reading netcdf files. The format of the data is provided in a dedicated chapter ("The Products format").

80 Page : Visualize the data GlobColour mapped products ( L3m ) can be visualized using tools accepting NetCDF format, such as BEAM / Visat 1 (Figure 5-6) and ncview 2 (Figure 5-7). Figure 5-6: Visualization of a GlobColour L3m product using Visat Figure 5-7: Visualization of a GlobColour L3m product using ncview. The following example shows how the Land flag can be used to depict the Earth mask with matplotlib (http://matplotlib.org/index.html)

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